项目介绍

2024年11月7日

The EcoVisionLab in the Department of Mathematical Modeling and Machine Learning (DM3L) at University of Zurich is seeking applications for a Doctoral Candidate in computer vision and machine learning for multimodal analysis of green spaces and nature to assess environmental and societal well-being in densely populated areas.

We offer an exciting and stimulating environment to study and work in. The University of Zurich has several internationally recognized research groups dedicated to data science, machine learning and remote sensing. We also collaborate with several other institutions and companies in the fields of computer vision, machine learning and earth observation, in Switzerland and abroad. The EcoVision Lab is member of the UZH Digital Society Initiative, the ETH AI Center, the new UN-ETH partnership, and the ETH for Development Center (ETH4D).

Your responsibilities

The successful candidate will work on a project in the EcoVision Lab in cooperation with a large project consortium to build a Public Data Lab for measuring societal wellbeing under changing circumstances together with more partners from the University of Zurich, the Statistical Office of the Canton of Zurich, and the Zurich University of the Arts. Emphasis for the doctoral project is on developing deep learning and computer vision methods to jointly analyse street-view and depth imagery, aerial and terrrestrial laser scans, satellite imagery etc. in combination with auxiliary map layers provided by the project partners, cantonal and federal Swiss agencies to come up with dense, high-resolution, spatially explicit indicators of green spaces with emphasis on societal and environmental well-being. Potential indicator domains include biomass, vegetation density, plant species, plant health etc. while project leaves ample room to explore various exciting technical avenues like uncertainty quantification, interpretability, and explainability in deep neural networks, attention-based approaches, text-to-image/point cloud translation, or diffusion models, for example.

Your profile

We are looking for candidates with an interest in performing innovative research, strong motivation, and an interest in software development. An ideal candidate will have:

• an excellent degree (M.Sc. or equivalent) in Computer Science, Machine Learning, or a related field (e.g. Electrical Engineering, Applied Mathematics)
• strong mathematical understanding
• experience in programming, preferably in Python, and engineering
• prior experience in machine learning, computer vision and remote sensing

Furthermore, the candidate should be fluent in English, both written and spoken.

Information on your application

Please submit your complete application (motivation letter, curriculum vitae, school and university score records, contact details of at least two referees) via the link below. The deadline for applications is 16 December 2024 and the desired starting date is 1 June 2025. Selection will start immediately, so early submissions are encouraged.

Further information

Questions about the job

Jan Dirk WegnerProfessor